Running Your Database in the Cloud Eran Levin VP R&D - Xeround

Agenda The paradigm shift Real life use case Challenges running a database in the cloud Available solutions Q&A

The Paradigm Shift From  Dedicated  On premise  Over provisioned  Self managed Without compromising functionality, performance, availability, … To  Shared resources  Cloud hosted  Pay-per-use  Managed service

The Paradigm Shift The Cloud  Availability issues  Stateless  Limited control (HW, Virtualization, Networking)  Expectations (reduce capital and operational costs) Databases  Mission critical, lossless  Statefull  Usage patterns (data and throughput)

Use Case eCommerce Application

Architectural Evolution - Rollout You are ready to roll your new eCommerce app Will deploy in the cloud (price, time to market, flexibility, “cool”)

Arch. Evolution - Failover Active Passive

Arch. Evolution – Traffic Increase Load Balancer

Arch. Evolution – Application Scaling Load Balancer

Arch. Evolution – Database Failover ActivePassive Load Balancer

Arch. Evolution – DB Read Scaling Master R R R Load Balancer

Architectural Evolution – DB Write Scaling Master R R R Load Balancer

Arch. Evolution – Anticipating the Peak Master R R R Load Balancer R R

Arch. Evolution – Scaling Down Master R R R Load Balancer

Arch. Evolution – Version Upgrade Master R R R Load Balancer Master R R R Load Balancer

Running Your Database in the Cloud The Challenges

The Challenges Availability Elasticity Manageability Cost  Solved for the Web and application levels  Imagine an equivalent solution for your database…

Meeting the Challenges Build your own  For example - MySQL on EC2, Postgres on Rackspace, …  Acquire instances  Install the database according to your architecture  Self manage your database Database-as-a-Service  For example - Amazon RDS, Xeround, Database.com, …

The Challenges Availability

Availability Standby machine Replication Failover mechanism Source:

Cloud Availability Solutions Amazon RDS Multi Zone  Master – Slave configuration  Up to 3 minutes recovery  Double the cost  Maintenance window Xeround  “Master-Master” configuration  Multiple replicas of the data  Always-on

The Challenges Scalability

Scalability – Scale Up vs. Scale Out Scale Up  Select next available configuration (EC2, RDS)  Relatively simple but limited scalability Scale Out  Add additional resources  Complicated but high scalability  RDS Read replicas Source:

Shared Everything vs. Shared Nothing Shared Everything  Scale throughput but limited due to shared resources  Storage and networking limitations in the cloud  ScaleDB Shared Nothing  Horizontal data partition / sharding  Unlimited scalability  Many design and implementation challenges

Shared Nothing in the Cloud Xeround  Virtual partitioning – decoupling of data and resources  Linear scalability for both reads and writes  Automatic balancing and repartition following changes in data and / or resources with no downtime ScaleBase / dbShards  Automatically partition the data and direct queries to right databases  Original databases deployment, management and cost  Partitioning events MySQL Cluster  NOT supported on virtual environments

Elasticity Scaling out/up AND in/down One of the Cloud justifications (but what about databases)

The Challenges Manageability

Manageability Self-serve is a fundamental characteristic of cloud computing DBaaS should provide  User management  DB management  Control and Monitoring  Backup and restore ……  API to enable extendibility and interaction with the cloud ecosystem Solutions: Amazon RDS, Xeround, FathomDB

Build Your Own Source:

Database as a Service

The Challenges Cost

Cost Pay-per-use is another fundamental characteristic of cloud computing Achieving this model requires:  Elasticity – scale resources according to actual usage  No over provisioning  No idle standby machines  Sharing resources to share cost  Measuring exact usage

Q & A

Running Your Database in the Cloud Thank You Visit us in Booth 407